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| import streamlit as st | |
| import faiss | |
| import numpy as np | |
| from sentence_transformers import SentenceTransformer | |
| st.title("WattBot RAG Assistant") | |
| embed_model = SentenceTransformer("all-MiniLM-L6-v2") | |
| question = st.text_input("Ask a sustainability question") | |
| if question: | |
| st.write("Processing...") | |
| embedding = embed_model.encode([question]) | |
| st.write("Embedding generated.") | |
| st.write("⚠️ Full RAG logic should be connected here.") |